University of Cambridge > Talks.cam > Computer Laboratory Systems Research Group Seminar > Latency-driven Performance in Data Centres

Latency-driven Performance in Data Centres

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Data centre-based cloud computing has revolutionised the way businesses use computing infrastructure. Instead of building their own data centres, companies rent computing resources and deploy their applications on cloud hardware. Providing customers with well-defined application performance guarantees is of paramount importance to ensure transparency and to build a lasting collaboration between users and cloud operators. A user’s application performance is subject to the constraints of the resources it has been allocated and to the impact of the network conditions in the data centre. Firstly, I show how to use the Precision Time Protocol (PTP), through an open-source software implementation PTPd, to measure network conditions. I propose PTPmesh, which uses PTPd, as a cloud network monitoring tool for tenants. Furthermore, I conduct a measurement study using PTPmesh in different cloud providers, finding that network latency variability in data centres is still common. Normal latency values in data centres are in the order of tens or hundreds of microseconds, while unexpected events, such as network congestion or packet loss, can lead to latency spikes in the order of milliseconds. Secondly, I show that network latency matters for certain distributed applications even in small amounts of tens or hundreds of microseconds, significantly reducing their performance. Given the network latency variability observed in data centres, applications’ performance is determined by their placement within the data centre. Thirdly, I propose latency-driven, application performance-aware, cluster scheduling as a way to provide performance guarantees to applications. I introduce NoMora, a cluster scheduling architecture that leverages the predictions of application performance dependent upon network latency combined with dynamic network latency measurements taken between pairs of hosts in data centres to place applications, showing that NoMora improves application performance by choosing better placements than other scheduling policies.

Bio:

Diana Andreea Popescu is a postdoctoral researcher working on IoT, edge computing and data centre networking in the Systems Research Group at the University of Cambridge, Department of Computer Science and Technology. She completed her PhD in Computer Science with a dissertation titled “Latency-driven performance in data centres” in the same group. She studied for her undergraduate degree in Computer Science at the University Politehnica of Bucharest, Romania, and for her master degree in Computer Science at École Polytechnique Fédérale de Lausanne, Switzerland. She interned several times at Google in the Network Infrastructure team and at CERN during her studies. Her research interests are data centre networking, network measurement, IoT and edge computing.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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